How AI Agents Are Creating Hyper-Personalized Experiences for Customers | Salesforce CIO Corner

I like to say we should all be very humble when we think about kind of gen AI. What are our constraints? Right. In some cases, the constraint is the business. There's a lot of preciousness of process. People don't want you to touch what they're doing. They're uncomfortable.

Hello, everyone. Welcome to CIO Corner. Here's where we will talk to IT leaders about the biggest challenges and opportunities that we all face when it comes to integrating technology into the enterprise. Today I'm joined by Mike Haidt, Chief Technology officer at Saks, a luxury fashion retailer that is using first party data and AI to drive personalized shopping experiences for their customers. Mike, it's awesome to see you here. Thank you for being here with us.

Thanks for having me. It's great to be here.

Many of us get introduced to these new technologies like generative AI through the use of our retailers websites. Yes. So give me a bit of a sense as to what you guys are working on when it comes to Genai in your specific cases, your interactions with customers. If I go to the SAX website and I actually decide that I want to buy a new blazor, will I be interacting with any type of gen AI technology?

Right now you'll be interacting with AI, that's for sure. The gen piece, I think, comes after it.

Comes after it, yeah. Yeah.

We're really using Genai heavily in the call center space. You know, our service agents are seeing summarized calls that allow for next best action so that you know, when you speak to a customer, you really can anticipate their needs and what they're looking for. We're seeing it a lot in our item setup. We take our own photos, which I think is uncommon, unusual, especially across an assortment of 500,000 items. There's some things that are working extremely well. Every now and then you'll generate a picture that has a nose on the forehead. So we're waiting incautiously, but we're excited about some of the early signals we're seeing across the entire experience.

That's great. And obviously you mentioned the customer service side. That to me is one of those areas where Genai AI in general will continue to influence the way that we do work. I worked for a CEO once. We used to say often that our mission when it came to using technology is to take the millions of customers that the the company was interacting with every single day and make each and every one of them feel like they were the only one.

Yes.

And that's personalization at its max. And I do believe to your Point that Gen AI Technologies will help us continue to get towards that objective. Right.

I think that we're getting to a place in this world where everybody is expecting a much more hyper personalized experience throughout their entire journey. How do you meet the customer where they want to be? Not just in their kind of browsing and discovery and purchase process, but after that fact.

I sit on the board of a public company and the conversations in the boardroom are, when it comes to AI, are becoming also more focused, are becoming more targeted as to, okay, yeah, there's all these great stuff around AI, but how are you bringing AI to life in the enterprise for use cases that will improve the customer experience or that will ultimately generate some kind of value through savings, efficiency, whatever that may be, that's not going to stop. And I think we need to be prepared to be able to handle those questions as they come our way because the boards will be all over this. Definitely the case.

A lot of the things that we found is that there's no shortcut to this space in this world. You know, you'll see a lot of people come and try and do things on top of a bad foundation build on top of bad data that generally doesn't work and it's really not going to scale in the way that you really want it to scale. So we've stubbed our toe a bunch. You know, we've kind of gone down a few paths that were really singular in purpose that didn't really have desired outcomes. And so what we've learned is just there should be a perpetual investment in data and infrastructure and modernization.

I know that many CIOs are actually now thinking, my goodness, I got, I want to implement AI, I want to do it tomorrow, right? But, but I got a data problem. I know you've been working diligently on this. How have you tackled it?

So we use low touch, low code tools to bring data into our data lake. We're bringing in 2 billion rows of data a day and taking advantage of that change in the market where storage is cheap, if you will, and easier, and really kind of building on top of that within a data lake itself, has proven to be extremely valuable. And I'd say the next step of that, which is why we're really excited about our partnership with Salesforce and Data Cloud and AgentForce, is finding ways to inject that data, to inject that customer DNA, to inject the decisions into the process. It's not always easy. You need platforms to do it. You know, some of the API work on Top data lakes, as you know, can be faulty and not scale in the best ways. And so we've engineered around that. But really we're at the point where I think our new constraint is where to inject that data versus how do we get data to a place and transform it and make use of it.

I love the way that you describe the customer DNA.

Right, yeah.

And for many years in retail, in transportation, where I came from, and in other industries, that customer DNA, we've only had a partial view of the entire DNA. But today we, with the technologies that exists and the capabilities that companies like Salesforce are building, we have the ability to bring data from all these different places together into creating a complete view of that DNA.

Absolutely. Yeah. I think the big change is that allows you to fail fast. Right. The days of needing a team, a massive team of Data engineers and DBAs to bring in a single new bespoke data source are gone. I think.

Yes.

You know, building a modernized data platform and leveraging data cloud really allows you to bring in things quickly, easily, you know, run some models against it, see if it provides any value and throw it away if it doesn't. And if it does, think about scaling it up.

Now I gotta ask you this question. We are here at Dreamforce. The major theme of our conference this year is all around agents. Yes, Agent force. The use of agents to improve a number of business processes through better interaction between humans, technology, being able to take actions through technology and ultimately really complement what humans do. You've been a huge proponent of this type of technology. Where are you in the agent journey?

We are really excited to say live with our first agent. I think kudos to the team. We were able to go from concept to live in about seven days.

Wow.

I'm hoping it's going to be on the agent leaderboard for some time to come. Yes. We picked some really great use cases where we have a large knowledge base. It's a more authentic conversation with the customer. Now we are getting toward the tail end of order management implementation, which I think getting service, commerce and order management together in one platform and then being able to leverage something like AgentForce to really leverage that data and action. That data is what's going to be.

A differentiator for us, especially in the retail world. Right. Where you know, you have these. All these different opportunities to improve the overall customer experience. Because you cannot always have a human that knows everything that needs to be known to provide that excellent customer experience. That's where, in my view, the agents come to play. Absolutely to actually help us generate a better customer experience at the app.

Yeah. And it allows us to meet the customer where they want to be. So there are times when the customer wants an extremely low friction interaction. You know, where is my order? Can I have an update on this? You know, there are times when you and I don't want to pick up the phone and talk to somebody. We just want an answer really quickly. Right. That's what the traditional kind of agent bots did. Sometimes you want a little bit more. Right. So you want to have a more complex conversation that, you know, there's not a decision tree for. That's really where we're leveraging agent force. We really believe that the human aspect is going to be much more meaningful. We can use our humans to do things like, you know, really high touch conversations with customers when there's something that needs a little bit more attention, if you will.

Yeah.

It also allows us to get into the space where we can put tools in the hands of service agents. And instead of just being a customer service representative, you're. You can sell your client telling, you're suggesting outfits to a consumer.

One of the things that I've enjoyed most about the conversation today is that usually when I speak about Gen AI with others, we start the conversation with productivity, with efficiency, with cost reduction. And we have been so passionate about using Gen AI for that that our minds normally go in that direction. But you started today with customer experiences, personalization, better customer interactions, meeting the customer where the customer wants to be met. I think that's an incredibly powerful message for our audience. Right. That, you know, Gen AI is not just about saving money. It's not just about cost. It's about creating that better customer connection. What you've convinced me of today, Mike, is that at the end of the day, these technologies will help us continue to move in that direction.

I believe so.

Awesome. Thank you so much for spending time with me. Thanks for having me immensely. Thank you, Mike. Well, please check out the links in the description below and be sure to stay tuned for more episodes of CIO Coin.